Multi-Task Learning papers, 2023–2026
Shared representations
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 1,181 papers are tagged with this topic.
Key findings
- Multi-Task Learning went from 288 papers in 2023 to 402 in 2026, roughly 1.4x in three years.
- NeurIPS publishes the most Multi-Task Learning work: 399 papers from 2023 to 2026, 34% of the four-venue total.
- The fastest-growing overlap is with Datasets and Benchmarks: papers tagged with both rose from 6 in 2023 to 16 in 2026.
- Among the 5 topics under Meta-Learning and Transfer, it ranks #2 by 2026 paper count; the fastest grower in the group, Foundation Model Adaptation, is up 3.8x versus 1.4x here.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 111 | 43 | 52 | 82 | 288 |
| 2024 | 61 | 31 | 58 | 77 | 227 |
| 2025 | 101 | 40 | 47 | 76 | 264 |
| 2026 | 126 | 57 | 91 | 128 | 402 |
Representative papers
Spread across years and venues so every edition shows up
- NeurIPS 2026A Mahalanobis Margin \texorpdfstring{$\gamma_{\min}$}{gamma\_min} Bound on Task Confusion in Pretrained Class-Incremental Learning: From Infeasibility to Exponential Attenuation
- ICML 2026A Systematic Study of Behavioral Cloning for Scientific Data Annotation
- ICLR 2026Automatic Stage Lighting Control: Is it a Rule-Driven Process or Generative Task?
- CVPR 20263D-Aware Multi-Task Learning with Cross-View Correlations for Dense Scene Understanding
- NeurIPS 2025A High-Dimensional Statistical Method for Optimizing Transfer Quantities in Multi-Source Transfer Learning
- ICML 2025ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning
- ICLR 2025CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding & Reasoning Capabilities of CodeLLMs
- CVPR 2025ACAttack: Adaptive Cross Attacking RGB-T Tracker via Multi-Modal Response Decoupling
- NeurIPS 2024CoMix: A Comprehensive Benchmark for Multi-Task Comic Understanding
- ICML 2024Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning
- ICLR 2024Class Incremental Learning via Likelihood Ratio Based Task Prediction
- CVPR 2024Differentiable Information Bottleneck for Deterministic Multi-view Clustering
- NeurIPS 2023A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm
- ICML 2023A Conditional Normalizing Flow for Accelerated Multi-Coil MR Imaging
- ICLR 2023An Extensible Multi-modal Multi-task Object Dataset with Materials
- CVPR 2023AMT: All-Pairs Multi-Field Transforms for Efficient Frame Interpolation
- NeurIPS 2026A Scalable Multi-Task Model for Virtual Sensors
- ICML 2026Alleviating Observation Bias via Causal-Invariant Meta-Learning for Unbalanced Incomplete Multi-view Clustering
- ICLR 2026Beyond Hearing: Learning Task-agnostic ExG Representations from Earphones via Physiology-informed Tokenization
- CVPR 2026Any Resolution Any Geometry From Multi-View To Multi-Patch
All Multi-Task Learning papers
399 papers, page 5 of 8
- NeurIPS 2025PROFIT: A Specialized Optimizer for Deep Fine Tuning
- NeurIPS 2025Prompt Tuning Decision Transformers with Structured and Scalable Bandits
- NeurIPS 2025Provably Efficient Multi-Task Meta Bandit Learning via Shared Representations
- NeurIPS 2025Quantifying Task-relevant Similarities in Representations Using Decision Variable Correlations
- NeurIPS 2025RadarQA: Multi-modal Quality Analysis of Weather Radar Forecasts
- NeurIPS 2025RAM-W600: A Multi-Task Wrist Dataset and Benchmark for Rheumatoid Arthritis
- NeurIPS 2025ReID5o: Achieving Omni Multi-modal Person Re-identification in a Single Model
- NeurIPS 2025RePIC: Reinforced Post-Training for Personalizing Multi-Modal Language Models
- NeurIPS 2025RNNs perform task computations by dynamically warping neural representations
- NeurIPS 2025RobustMerge: Parameter-Efficient Model Merging for MLLMs with Direction Robustness
- NeurIPS 2025SAINT: Sequence-Aware Integration for Spatial Transcriptomics Multi-View Clustering
- NeurIPS 2025Same Task, Different Circuits: Disentangling Modality-Specific Mechanisms in VLMs
- NeurIPS 2025Scalable Cross-View Sample Alignment for Multi-View Clustering with View Structure Similarity
- NeurIPS 2025Scaling Image Geo-Localization to Continent Level
- NeurIPS 2025SIFusion: A Unified Fusion Framework for Multi-granularity Arctic Sea Ice Forecasting
- NeurIPS 2025Single GPU Task Adaptation of Pathology Foundation Models for Whole Slide Image Analysis
- NeurIPS 2025SMARTraj$^2$: A Stable Multi-City Adaptive Method for Multi-View Spatio-Temporal Trajectory Representation Learning
- NeurIPS 2025Soft Task-Aware Routing of Experts for Equivariant Representation Learning
- NeurIPS 2025SynCL: A Synergistic Training Strategy with Instance-Aware Contrastive Learning for End-to-End Multi-Camera 3D Tracking
- NeurIPS 2025Task-Optimized Convolutional Recurrent Networks Align with Tactile Processing in the Rodent Brain
- NeurIPS 2025Task-Specific Data Selection for Instruction Tuning via Monosemantic Neuronal Activations
- NeurIPS 2025Theory-Driven Label-Specific Representation for Incomplete Multi-View Multi-Label Learning
- NeurIPS 2025Towards Minimizing Feature Drift in Model Merging: Layer-wise Task Vector Fusion for Adaptive Knowledge Integration
- NeurIPS 2025TS-MOF: Two-Stage Multi-Objective Fine-tuning for Long-Tailed Recognition
- NeurIPS 2025Unbiased Prototype Consistency Learning for Multi-Modal and Multi-Task Object Re-Identification
- NeurIPS 2025VaMP: Variational Multi-Modal Prompt Learning for Vision-Language Models
- NeurIPS 2025Where Graph Meets Heterogeneity: Multi-View Collaborative Graph Experts
- NeurIPS 2024$C^2M^3$: Cycle-Consistent Multi-Model Merging
- NeurIPS 2024$SE(3)$ Equivariant Ray Embeddings for Implicit Multi-View Depth Estimation
- NeurIPS 2024A New Neural Kernel Regime: The Inductive Bias of Multi-Task Learning
- NeurIPS 2024A Swiss Army Knife for Heterogeneous Federated Learning: Flexible Coupling via Trace Norm
- NeurIPS 2024Adversarially Robust Multi-task Representation Learning
- NeurIPS 2024AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers
- NeurIPS 2024Autonomous Agents for Collaborative Task under Information Asymmetry
- NeurIPS 2024BAKU: An Efficient Transformer for Multi-Task Policy Learning
- NeurIPS 2024Beyond task diversity: provable representation transfer for sequential multitask linear bandits
- NeurIPS 2024CoMix: A Comprehensive Benchmark for Multi-Task Comic Understanding
- NeurIPS 2024CONTRAST: Continual Multi-source Adaptation to Dynamic Distributions
- NeurIPS 2024Customized Multiple Clustering via Multi-Modal Subspace Proxy Learning
- NeurIPS 2024DeTeCtive: Detecting AI-generated Text via Multi-Level Contrastive Learning
- NeurIPS 2024Efficiency for Free: Ideal Data Are Transportable Representations
- NeurIPS 2024Efficient Multi-task LLM Quantization and Serving for Multiple LoRA Adapters
- NeurIPS 2024Efficient Multi-task Reinforcement Learning with Cross-Task Policy Guidance
- NeurIPS 2024EMR-Merging: Tuning-Free High-Performance Model Merging
- NeurIPS 2024Evaluate then Cooperate: Shapley-based View Cooperation Enhancement for Multi-view Clustering
- NeurIPS 2024Exploring the Precise Dynamics of Single-Layer GAN Models: Leveraging Multi-Feature Discriminators for High-Dimensional Subspace Learning
- NeurIPS 2024Extending Multi-modal Contrastive Representations
- NeurIPS 2024Flexible task abstractions emerge in linear networks with fast and bounded units
- NeurIPS 2024GAMap: Zero-Shot Object Goal Navigation with Multi-Scale Geometric-Affordance Guidance
- NeurIPS 2024Generative Retrieval Meets Multi-Graded Relevance
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FAQ
- How many Multi-Task Learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?
- 1,181 in total: 288 in 2023, 227 in 2024, 264 in 2025, 402 in 2026.
- How many Multi-Task Learning papers are at NeurIPS 2026?
- NeurIPS 2026 has 126 Multi-Task Learning papers, versus 101 the year before.
- How many Multi-Task Learning papers are at ICLR 2026?
- ICLR 2026 has 57 Multi-Task Learning papers, versus 40 the year before.
- How many Multi-Task Learning papers are at ICML 2026?
- ICML 2026 has 91 Multi-Task Learning papers, versus 47 the year before.
- How many Multi-Task Learning papers are at CVPR 2026?
- CVPR 2026 has 128 Multi-Task Learning papers, versus 76 the year before.
- Which conference publishes the most Multi-Task Learning papers?
- NeurIPS, with 399 papers from 2023 to 2026.